Hybrid Video Encoding Mode Switching for Noise Resilience
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Solution Overview
Problem
Current video processing technologies face challenges in efficiently encoding and decoding video image data, particularly in hybrid encoding and decoding methods for single and multiple layered video coding systems, where residual information is difficult to predict due to noise and decorrelation issues, leading to suboptimal coding efficiency and quality.
Innovation Solution
The proposed method involves adaptive switching between residual coding and picture coding modes, using disparity estimation and compensation, transformation, quantization, and entropy encoding to generate bitstreams, and includes a reference processing unit (RPU) for improved prediction and encoding of residual signals, allowing for efficient encoding and decoding of video data across layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If residual coding mode is used for encoding video data, then compression efficiency is improved, but prediction accuracy deteriorates due to noise and decorrelation issues
Solution Approach 1:
The system dynamically switches between residual coding mode and picture coding mode based on prediction accuracy assessment. When prediction accuracy falls below a threshold due to noise and decorrelation, the system transitions from residual coding to picture coding, and vice versa, optimizing compression efficiency while maintaining prediction accuracy.
Solution Approach 2:
The system changes the coding parameter (coding mode) adaptively based on the characteristics of the video data being encoded. By monitoring prediction accuracy metrics and switching between different coding modes (residual vs. picture coding), the system optimizes the balance between compression efficiency and prediction accuracy for different regions and time periods.
2Productivity
If adaptive switching between coding modes is implemented, then coding efficiency is improved, but system complexity increases
Solution Approach 1:
The video encoding process is segmented into distinct coding modes (residual coding and picture coding) that can be independently evaluated and switched between. This segmentation allows the system to apply the most appropriate coding mode to different regions or time periods, improving overall coding efficiency while managing complexity through modular design.
Solution Approach 2:
The system performs self-assessment of prediction accuracy and automatically switches between coding modes without requiring complex external control. The encoding system monitors its own performance metrics and makes adaptive decisions, reducing the need for complex external management while improving coding efficiency.
Data Source
AI summary
Encoding and decoding methods for single and multiple layered video coding systems are provided. Specifically, video information provided to a base layer and one or more enhancement layers can be coded using a picture coding mode and/or a residual coding mode. Selection between coding modes can be performed on a region-by-region basis.